Question 1

How do I set up libpython-clj with Anaconda or Conda?

Accepted Answer

You need to specify the Python executable and library paths from your Conda environment during `py/initialize!`, as shown in the config namespace example. The library dynamically discovers libraries, but manual configuration is often required for Conda setups.

Question 2

What's the difference between dynamic and static calls in libpython-clj?

Accepted Answer

Dynamic calls use `require-python` for runtime import but have slower performance; static code generation creates Clojure namespaces for faster loading and AOT compilation, as detailed in the static code generation feature.

Question 3

libpython-clj vs GraalVM for Python interop in Clojure?

Accepted Answer

libpython-clj offers deep, REPL-oriented integration with existing Python installations, while GraalVM provides native compilation but may have limitations with Python libraries. libpython-clj is better for leveraging Conda and NumPy directly.

Question 4

How to generate static Clojure wrappers for Python modules?

Accepted Answer

Use the `write-namespace!` function from the codegen module to create Clojure namespaces that wrap Python modules, improving performance and enabling AOT compilation, as referenced in the static code generation section.

Question 5

Does libpython-clj work on Windows with Python 3.8 or newer?

Accepted Answer

Yes, it supports multiple Python versions and environments, including Windows, but you may need to manually set library paths if automatic discovery fails, as mentioned in the environments documentation.

Question 6

Can I use libpython-clj from Java without Clojure?

Accepted Answer

Yes, there's a Java API included that allows efficient data copies and callbacks, but you must manage the GIL manually for some methods, as noted in the Java API documentation.

Libpython-clj

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